Atrial fibrillation (AF) and ventricular tachycardia (VT) affect millions of patients in the United States. These arrhythmias can be cured with catheter ablation, but the arrhythmias often recur, and these recurrences are generally due to reversible conduction block from incomplete ablation. The inability to confirm the presence of completely ablated lesions in the desired locations is the major factor in the greater than 40% recurrence of VT after ablation, and the greater than 30 % recurrence of AF after ablation. In addition, it is not possible with current technology to adequately predict the pathways of VT through scar, which are the targets for ablation. The overall goal of this project is to combine high resolution Magnetic Resonance Imaging (MRI) and limited invasive mapping, with fast computational modeling, to predict arrhythmia circuits and targets for ablation. This goal includes using this technology to update ablation targets during a procedure to allow for identification and ablation of any remaining arrhythmogenic substrate as ablation is proceeding. We hypothesize that computational modeling, optimized with high-resolution MRI, and limited invasive mapping, can (1) aid in predicting the locations of arrhythmia circuits (2) aid in predicting the locations of critical ablation targets, and (3) aid in assessing the completeness of ablation. Once validated, these enhanced capabilities could help to dramatically improve the outcomes from complex ablations, become part of ablation methods of the future, and become a platform for improving outcomes from other interventions. We have already developed improved high resolution imaging methods that allow accurate differentiation of infarct scar and border zone from normal tissue. This high resolution imaging may also allow for detection of conducting channels that may be present in otherwise dense scar, and which may be a critical part of some VT circuits. We are also pursuing limited invasive mapping as a means to detect the presence of late potentials in scar to aid in the detection and/or verification of conducting channels, which may be difficult to identify with current MRI methods. We will further improve high resolution imaging for input for a computational model that along with the detection and/or confirmation of conduction channels from invasive mapping, will predict arrhythmia circuit locations, and allow the fast and accurate determination of optimal targets for ablation. In addition, since the model can be run in near real time, and since we can perform intra-procedure MRI, we will also study the use of the computational model for predicting when additional ablation is needed to complete the ablation of all arrhythmogenic substrate. Finally, we have developed imaging methods that differentiate incompletely ablated (reversibly damaged) tissue from completely ablated (necrotic) tissue. If ablation of some lesions is found to be incomplete during a procedure, additional ablation can be performed to complete the ablation, and likely substantially reduce arrhythmia recurrences. This project is a collaboration between the Johns Hopkins University (High Resolution MRI, invasive mapping), and Siemens (computational modeling).